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on MENA - Middle East and North Africa |
| By: | Sinem Ayhan (Leibniz-Institute for East and Southeast European Studies (IOS) & IZA); Hartmut Lehmann (Leibniz-Institute for East and Southeast European Studies (IOS), University of Regensburg & IZA); Selin Pelek (Leibniz-Institute for East and Southeast European Studies (IOS), University of Regensburg & IZA) |
| Abstract: | This paper examines the dynamics of Turkey’s labor market using job flow analysis. We analyze administrative data from 2006 to 2021, encompassing all non-financial firms and their employees registered with social security institutions, to examine employment dynamics during various periods, including significant shocks like the 2008 global recession, the local currency collapse in late 2018, and the first two years of the COVID-19 pandemic. We examine how an extended set of firm characteristics influences employment structure dynamics. Turkey’s labor market is highly dynamic, with job reallocation rates ranging from 34% to 44%, surpassing Anglo-Saxon nations and significantly exceeding transition countries, but having similar rates of developing countries. High excess job reallocation rates reveal substantial and genuine job structure changes in Turkey, especially notable in the construction sector, where job creation persistence is remarkably low. Micro firms (up to 10 employees) dominate job creation and destruction, with declining job flow rates as firms grow larger or older. Low-tech industries in manufacturing display a similar pattern, contributing significantly to job creation and destruction. Firms strongly engaged in imports and/or exports also contribute more to job creation and job destruction compared to those with low exposure to international trade. |
| Keywords: | Job creation, job destruction, firm characteristics, administrative data, Turkey |
| JEL: | E24 J08 J23 J63 L25 L26 |
| Date: | 2023–10 |
| URL: | https://d.repec.org/n?u=RePEc:ost:wpaper:402 |
| By: | Asef Yelghi; Aref Yelghi; Shirmohammad Tavangari |
| Abstract: | The development of artificial intelligence has made significant contributions to the financial sector. One of the main interests of investors is price predictions. Technical and fundamental analyses, as well as econometric analyses, are conducted for price predictions; recently, the use of AI-based methods has become more prevalent. This study examines daily Dollar/TL exchange rates from January 1, 2020, to October 4, 2024. It has been observed that among artificial intelligence models, random forest, support vector machines, k-nearest neighbors, decision trees, and gradient boosting models were not suitable; however, multilayer perceptron and linear regression models showed appropriate suitability and despite the sharp increase in Dollar/TL rates in Turkey as of 2019, the suitability of valid models has been maintained. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.04259 |